A Discussion of “Text Selection”

Nitish Ranjan Sinha

Journal of Business & Economic Statistics, 2021, vol. 39, issue 4, 888-891

Abstract: Kelly, Manela, and Moreira provided an economic model of word choice in text. A writer is modeled as someone who is first choosing whether to use a word at all (selection problem) and then deciding how often a selected word should be used (positive counts problem). The resulting model leads to better sufficient reduction for large number of words/phrases in the text as demonstrated many diverse applications that use information captured from the text of the front page of the Wall Street Journal such as back-casting regulatory capital ratio of banks, and forecasting and nowcasting U.S. macroeconomic variables. Researchers interested in quantifying information in text will benefit from reading the article and thinking about some of the issues raised in the article. I provide background, context from other foundational papers, a very short summary of the article, and make some broad observations in my discussion.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2021.1961785 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:39:y:2021:i:4:p:888-891

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20

DOI: 10.1080/07350015.2021.1961785

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan

More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().